A Perspective on Correlation-Based Financial Networks and Entropy Measures

被引:15
|
作者
Kukreti, Vishwas [1 ]
Pharasi, Hirdesh K. [2 ]
Gupta, Priya [3 ]
Kumar, Sunil [4 ]
机构
[1] Jawaharlal Nehru Univ, Sch Computat & Integrat Sci, New Delhi, India
[2] Univ Nacl Autonoma Mexico, Inst Ciencias Fis, Cuernavaca, Morelos, Mexico
[3] Jawaharlal Nehru Univ, Atal Bihari Vajpayee Sch Management & Entrepreneu, New Delhi, India
[4] Univ Delhi, Ramjas Coll, Dept Phys, New Delhi, India
来源
FRONTIERS IN PHYSICS | 2020年 / 8卷
关键词
econophysics; random matrix theory; correlation; networks; minimum spanning trees; clustering; financial networks; HIERARCHICAL STRUCTURE; COMPLEX NETWORKS; INFORMATION; MULTISCALE; NOISE;
D O I
10.3389/fphy.2020.00323
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In this mini-review, we critically examine the recent work done on correlation-based networks in financial systems. The structure of empirical correlation matrices constructed from the financial market data changes as the individual stock prices fluctuate with time, showing interesting evolutionary patterns, especially during critical events such as market crashes, bubbles, etc. We show that the study ofcorrelation-based networksand their evolution with time is useful for extracting important information of the underlying market dynamics. Also, we present our perspective on the use of recently-developed entropy measures, such asstructural entropyandeigen-entropy, for continuous monitoring of correlation-based networks.
引用
收藏
页数:7
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